---
title: "Pilot Data 2020"
output:
flexdashboard::flex_dashboard:
orientation: columns
social: menu
source_code: embed
vertical_layout: scroll
theme: spacelab
---
```{r setup, include=FALSE}
library(flexdashboard)
library(tidyverse)
library(rio)
library(here)
library(colorblindr)
library(gghighlight)
library(forcats)
library(ggrepel)
library(gt)
library(knitr)
library(kableExtra)
library(reactable)
library(plotly)
opts_chunk$set(echo = FALSE,
fig.width = 5,
fig.height = 6)
theme_set(theme_minimal(base_size = 8))
outcome <- import(here("data", "client_data_outcome.sav"),
setclass = "tbl_df") %>%
characterize() %>%
janitor::clean_names()
rm_prge <- import(here("data", "repeated_measures_prge.sav"),
setclass = "tbl_df") %>%
characterize() %>%
janitor::clean_names()
head(outcome)
head(rm_prge)
rm_drkat <- import(here("data", "drkat_rm.xlsx"),
setclass = "tbl_df") %>%
janitor::clean_names()
head(rm_drkat)
brief_data <- import(here("data", "brief_pilot_data.xlsx"),
setclass = "tbl_df") %>%
janitor::clean_names()
head(brief_data)
falo_rm <- import(here("data", "falo_rm.xlsx"),
setclass = "tbl_df") %>%
janitor::clean_names()
```
# PRGE Outcome
Column {.tabset data-width=650}
-----------------------------------------------------------------------
```{r outcome measures data organization, include=FALSE}
head(outcome)
brief <- outcome %>%
filter(client == "PRGE") %>%
select(1, c(16:31))
brief_prge <- brief %>%
select(client, brief_eri_pre_self, brief_eri_post_self, brief_eri_pre_inf, brief_eri_post_inf)
brief_tidy <- brief_prge %>%
rename("Self Pre ERI" = brief_eri_pre_self,
"Self Post ERI" = brief_eri_post_self,
"Parent Pre ERI" = brief_eri_pre_inf,
"Parent Post ERI" = brief_eri_post_inf) %>%
pivot_longer(
cols = c(2:5),
names_to = "measure",
values_to = "score"
)
prge_brief_parent <- brief_data %>%
filter(client == "PRGE") %>%
select(client, 8, 9, 16, 17) %>%
rename("SM Pre" = self_monitor_pre_parent,
"SM Post" = self_monitor_post_parent,
"EC Pre" = emotional_control_pre_parent,
"EC Post" = emotional_control_post_parent) %>%
pivot_longer(
cols = c(2:5),
names_to = "measure",
values_to = "score"
)
prge_parent <- c("SM Pre",
"SM Post",
"EC Pre",
"EC Post")
class <- outcome %>%
filter(client == "PRGE") %>%
select(client, class_total_pre, class_total_post) %>%
rename("Pre Score" = class_total_pre,
"Post Score" = class_total_post)
class_tidy <- class %>%
pivot_longer(
cols = c(2:3),
names_to = "measure",
values_to = "score"
)
symptoms <- outcome %>%
filter(client == "PRGE") %>%
select(1, c(6:13)) %>%
rename("Feeling Slow Pre" = pcss_pre_feeling_slow,
"Feeling Slow Post" = pcss_post_feeling_slow,
"Feeling Foggy Pre" = pcss_pre_feeling_foggy,
"Feeling Foggy Post" = pcss_post_feeling_foggy,
"Difficulty Concentrating Pre" = pcss_pre_difficulty_concentrating,
"Difficulty Concentrating Post" = pcss_post_difficulty_concentrating,
"Difficulty Remembering Pre" = pcss_pre_difficulty_remembering,
"Difficulty Remembering Post" = pcss_post_difficulty_remembering) %>%
pivot_longer(
cols = c(2:9),
names_to = "measure",
values_to = "score"
)
hit <- outcome %>%
filter(client == "PRGE") %>%
select(client, hit_pre, hit_post) %>%
rename("Pre Score" = hit_pre,
"Post Score" = hit_post) %>%
pivot_longer(
cols = c(2:3),
names_to = "measure",
values_to = "score"
)
```
```{r outcome plots, include=FALSE}
#geom_rect(aes(xmin = -Inf, xmax = Inf, ymin = 65, ymax = 100),
#fill = "lightgreen") + #insert before geom_col
prge_brief <- c("Self Pre ERI",
"Self Post ERI",
"Parent Pre ERI",
"Parent Post ERI")
class_positions <- c("Pre Score", "Post Score")
pcss_positions <- c("Difficulty Remembering Post",
"Difficulty Remembering Pre",
"Difficulty Concentrating Post",
"Difficulty Concentrating Pre",
"Feeling Foggy Post",
"Feeling Foggy Pre",
"Feeling Slow Post",
"Feeling Slow Pre")
hit_positions <- c("Pre Score", "Post Score")
p1 <- ggplot(brief_tidy, aes(measure, score)) +
geom_hline(yintercept = 65,
linetype = "dashed",
size = 1) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = prge_brief) +
scale_y_continuous(limits = c(0, 100),
breaks = c(10, 20, 30, 40, 50, 60, 70, 80, 90, 100)) +
geom_text(aes(measure, score, label = score),
nudge_y = -3,
color = "white") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
plot.subtitle = element_text(color = "black", size = 10, face = "bold"),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10),
plot.caption = element_text(size = 10)) +
labs(x = "",
y = "T-score",
title = "BRIEF Scores",
subtitle = "Emotion Regulation Index",
caption = "T-scores Above 65 are Clinically Significant")
prge_parent_graph <- ggplot(prge_brief_parent, aes(measure, score)) +
geom_hline(yintercept = 65,
linetype = "dashed",
size = 1) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = prge_parent) +
scale_y_continuous(limits = c(0, 100),
breaks = c(10, 20, 30, 40, 50, 60, 70, 80, 90, 100)) +
geom_text(aes(measure, score, label = score),
nudge_y = -3,
color = "white") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
plot.subtitle = element_text(color = "black", size = 10, face = "bold"),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10),
plot.caption = element_text(size = 10)) +
labs(x = "",
y = "T-score",
title = "BRIEF Scores",
subtitle = "Parent Responses to the Self-Monitor and Emotional Control Scales",
caption = "T-scores Above 65 are Clinically Significant")
prge_parent_graph
p1
p2 <- ggplot(class_tidy, aes(measure, score)) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = class_positions) +
scale_y_continuous(limits = c(0, 60),
breaks = c(10, 20, 30, 40, 50, 60)) +
geom_text(aes(measure, score, label = score),
nudge_y = -3,
color = "white") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "",
y = "Score",
title = "CLASS Scores")
p2
p3 <- ggplot(symptoms, aes(measure, score)) +
geom_hline(yintercept = 30,
linetype = "dashed",
size = 1) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = pcss_positions) +
scale_y_continuous(limits = c(0, 6),
breaks = c(0, 1, 2, 3, 4, 5, 6)) +
coord_flip() +
geom_text(aes(measure, score, label = score),
nudge_y = -0.5,
color = "white") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
plot.subtitle = element_text(color = "black", size = 10, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10),
plot.caption = element_text(size = 10)) +
labs(x = "",
y = "Score",
title = "PCSS Results",
subtitle = "Cognitive Symptoms",
caption = "0 = No Symptoms\n 3 = Moderate Symptoms\n 6 = Severe Symptoms")
p3
p3a <- ggplot(hit, aes(measure, score)) +
geom_hline(yintercept = 50,
linetype = "dashed",
size = 1) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = hit_positions) +
scale_y_continuous(limits = c(0, 60),
breaks = c(10, 20, 30, 40, 50, 60)) +
geom_text(aes(measure, score, label = score),
nudge_y = -3,
color = "white") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10),
plot.caption = element_text(size = 10)) +
labs(x = "",
y = "Score",
title = "HIT Results",
caption = "Scores of 50 or Greater Suggest Headaches Impact Daily Functioning")
p3a
```
### BRIEF Client-Parent Responses
```{r prge brief, include=TRUE}
p1
```
### BRIEF Parent Responses
```{r prge parent brief, include=TRUE}
prge_parent_graph
```
### CLASS
```{r prge class, include=TRUE}
p2
```
### PCSS
```{r prge pcss, include=TRUE}
p3
```
### HIT
```{r prge hit, include=TRUE}
p3a
```
Column {data-width=350}
-----------------------------------------------------------------------
### Client Demographics
```{r, include=FALSE}
head(outcome)
demo_prge <- outcome %>%
filter(client == "PRGE") %>%
select(2:5)
head(demo_prge)
prge_table <- demo_prge %>%
gt() %>%
cols_label(sex = "Sex",
age = "Age",
prev_mtbi = "Prior Concussions",
hx_depression = "History of Depression or Anxiety") %>%
cols_align(align = "center", columns = vars(sex, age, prev_mtbi, hx_depression)) %>%
tab_header(title = "Client Demographics")
prge_table
```
```{r prge table, include=TRUE}
prge_table
```
# PRGE Repeated
Column {.tabset data-width=650}
-----------------------------------------------------------------------
### Status Tracking
```{r repeated measures data cleaning, include=FALSE}
head(rm_prge)
track <- rm_prge %>%
select(session, status)
p4 <- ggplot(track, aes(session, status)) +
geom_line() +
geom_point(size = 2) +
scale_x_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
scale_y_continuous(limits = c(0, 6),
breaks = c(1, 2, 3, 4, 5, 6)) +
theme_classic() +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "Session",
y = "Number of Times Required to Reread Content",
title = "Status Tracking Goal")
p4
effort_data <- rm_prge %>%
select(session, effort)
p5 <- ggplot(effort_data, aes(session, effort)) +
geom_line() +
geom_point(size = 2) +
scale_x_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
scale_y_continuous(limits = c(0, 5),
breaks = c(1, 2, 3, 4, 5)) +
theme_classic() +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "Session",
y = "Perceived Effort During Reading",
title = "Perceived Effort While Reading",
caption = "1 = No Effort\n 2 = A little Effort\n 3 = Somewhat Effortful\n 4 = Quite Effortful\n 5 = Extremely Effortful")
p5
helpfulness <- rm_prge %>%
select(session, help)
p6 <- ggplot(helpfulness, aes(session, help)) +
geom_line() +
geom_point(size = 2) +
scale_x_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
scale_y_continuous(limits = c(0, 5),
breaks = c(1, 2, 3, 4, 5)) +
theme_classic() +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "Session",
y = "Perceived Helpfulness",
title = "Perceived Helpfulness of Reading Strategies",
caption = "1 = Not Helpful at All\n 2 = Not Helpful\n 3 = Somewhat Helpful\n 4 = Helpful\n 5 = Very Helpful")
p6
```
```{r status, include=TRUE}
p4
```
### Perceived Effort
```{r effort, include=TRUE, fig.align="left"}
p5
```
### Perceived Strategy Helpfulness
```{r helpfulness, include=TRUE, fig.align="left"}
p6
```
# FALO Outcome
Column {.tabset data-width=650}
-----------------------------------------------------------------------
```{r falo measures data organization, include=FALSE}
head(outcome)
falo <- outcome %>%
filter(client == "FALO")
falo_brief_self <- brief_data %>%
filter(client == "FALO") %>%
select(client,
working_memory_pre_self,
working_memory_post_self,
plan_organize_pre_sr,
plan_organize_post_sr,
task_monitor_pre_sr,
task_monitor_post_sr) %>%
rename("WM Pre" = working_memory_pre_self,
"WM Post" = working_memory_post_self,
"PO Pre" = plan_organize_pre_sr,
"PO Post" = plan_organize_post_sr,
"TM Pre" = task_monitor_pre_sr,
"TM Post" = task_monitor_post_sr) %>%
pivot_longer(
cols = c(2:7),
names_to = "measure",
values_to = "score"
)
falo_sr_brief <- c("WM Pre",
"WM Post",
"PO Pre",
"PO Post",
"TM Pre",
"TM Post")
falo_sr_plot <- ggplot(falo_brief_self, aes(measure, score)) +
geom_hline(yintercept = 65,
linetype = "dashed",
size = 1) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = falo_sr_brief) +
scale_y_continuous(limits = c(0, 100),
breaks = c(10, 20, 30, 40, 50, 60, 70, 80, 90, 100)) +
geom_text(aes(measure, score, label = score),
nudge_y = -3,
color = "white") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
plot.subtitle = element_text(color = "black", size = 10, face = "bold"),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10),
plot.caption = element_text(size = 10)) +
labs(x = "",
y = "T-score",
title = "BRIEF Scores",
subtitle = "Working Memory, Plan/Organize, and Task Monitoring Scales",
caption = "T-scores Above 65 are Clinically Significant")
falo_sr_plot
falo_brief_parent <- brief_data %>%
filter(client == "FALO") %>%
select(client,
working_memory_pre_parent,
working_memory_post_parent,
plan_organize_pre_parent,
plan_organize_post_parent,
task_monitor_pre_parent,
task_monitor_post_parent) %>%
rename("WM Pre" = working_memory_pre_parent,
"WM Post" = working_memory_post_parent,
"PO Pre" = plan_organize_pre_parent,
"PO Post" = plan_organize_post_parent,
"TM Pre" = task_monitor_pre_parent,
"TM Post" = task_monitor_post_parent) %>%
pivot_longer(
cols = c(2:7),
names_to = "measure",
values_to = "score"
)
falo_parent_plot <- ggplot(falo_brief_parent, aes(measure, score)) +
geom_hline(yintercept = 65,
linetype = "dashed",
size = 1) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = falo_sr_brief) +
scale_y_continuous(limits = c(0, 100),
breaks = c(10, 20, 30, 40, 50, 60, 70, 80, 90, 100)) +
geom_text(aes(measure, score, label = score),
nudge_y = -3,
color = "white") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
plot.subtitle = element_text(color = "black", size = 10, face = "bold"),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10),
plot.caption = element_text(size = 10)) +
labs(x = "",
y = "T-score",
title = "BRIEF Scores",
subtitle = "Working Memory, Plan/Organize, and Task Monitoring Scales",
caption = "T-scores Above 65 are Clinically Significant")
falo_parent_plot
class_falo <- falo %>%
select(client, class_total_pre, class_total_post) %>%
rename("Pre Score" = class_total_pre,
"Post Score" = class_total_post) %>%
pivot_longer(
cols = c(2:3),
names_to = "measure",
values_to = "score"
)
pcss_falo <- falo %>%
select(1, c(6:13)) %>%
rename("Feeling Slow Pre" = pcss_pre_feeling_slow,
"Feeling Slow Post" = pcss_post_feeling_slow,
"Feeling Foggy Pre" = pcss_pre_feeling_foggy,
"Feeling Foggy Post" = pcss_post_feeling_foggy,
"Difficulty Concentrating Pre" = pcss_pre_difficulty_concentrating,
"Difficulty Concentrating Post" = pcss_post_difficulty_concentrating,
"Difficulty Remembering Pre" = pcss_pre_difficulty_remembering,
"Difficulty Remembering Post" = pcss_post_difficulty_remembering) %>%
pivot_longer(
cols = c(2:9),
names_to = "measure",
values_to = "score"
)
hit_falo <- falo %>%
select(client, hit_pre, hit_post) %>%
rename("Pre Score" = hit_pre,
"Post Score" = hit_post) %>%
pivot_longer(
cols = c(2:3),
names_to = "measure",
values_to = "score"
)
```
```{r falo plots, include=FALSE}
p8 <- ggplot(class_falo, aes(measure, score)) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = class_positions) +
scale_y_continuous(limits = c(0, 60),
breaks = c(10, 20, 30, 40, 50, 60)) +
geom_text(aes(measure, score, label = score),
nudge_y = -3,
color = "white") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "",
y = "Score",
title = "CLASS Scores")
p8
p9 <- ggplot(pcss_falo, aes(measure, score)) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = pcss_positions) +
scale_y_continuous(limits = c(0, 6),
breaks = c(0, 1, 2, 3, 4, 5, 6)) +
geom_text(aes(measure, score, label = score),
nudge_y = -1,
color = "white") +
coord_flip() +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10),
plot.caption = element_text(size = 10)) +
labs(x = "",
y = "Score",
title = "PCSS Results",
subtitle = "Cognitive Symptoms",
caption = "0 = No Symptoms\n 3 = Moderate Symptoms\n 6 = Severe Symptoms")
p9
falo_pcss_table <- pcss_falo %>%
select(-client) %>%
gt() %>%
cols_label(measure = "PCSS Question",
score = "Response") %>%
cols_align(align = "left", columns = vars(measure)) %>%
cols_align(align = "center", columns = vars(score)) %>%
tab_header(title = "PCSS Results",
subtitle = "Cognitive Symptoms")
falo_pcss_table
falo_reactable <- pcss_falo %>%
select(-client) %>%
rename("PCSS Question" = measure,
"Response" = score) %>%
reactable()
falo_reactable
p10 <- ggplot(hit_falo, aes(measure, score)) +
geom_hline(yintercept = 50,
linetype = "dashed",
size = 1) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = hit_positions) +
scale_y_continuous(limits = c(0, 60),
breaks = c(10, 20, 30, 40, 50, 60)) +
geom_text(aes(measure, score, label = score),
nudge_y = -3,
color = "white") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10),
plot.caption = element_text(size = 10)) +
labs(x = "",
y = "Score",
title = "HIT Results",
caption = "Scores of 50 or Greater Suggest Headaches Significantly Impact Daily Functioning")
p10
```
### BRIEF Self Report
```{r falo brief, include=TRUE, fig.width=6}
falo_sr_plot
```
### BRIEF Parent Report
```{r falo brief parent, include=TRUE, fig.width=6}
falo_parent_plot
```
### CLASS
```{r falo class, include=TRUE, fig.width=6}
p8
```
### PCSS
```{r falo pcss, include=TRUE}
falo_pcss_table
```
### HIT
```{r falo hit, include=TRUE}
p10
```
Column {data-width=350}
-----------------------------------------------------------------------
### Client Demographics
```{r, include=FALSE}
head(outcome)
demo_falo <- outcome %>%
filter(client == "FALO") %>%
select(2:5)
head(demo_falo)
falo_table <- demo_falo %>%
gt() %>%
cols_label(sex = "Sex",
age = "Age",
prev_mtbi = "Prior Concussions",
hx_depression = "History of Depression or Anxiety") %>%
cols_align(align = "center", columns = vars(sex, age, prev_mtbi, hx_depression)) %>%
tab_header(title = "Client Demographics")
falo_table
```
```{r falo table, include=TRUE}
falo_table
```
# FALO Repeated
Column {.tabset data-width=650}
-----------------------------------------------------------------------
### Status Tracking 1
```{r falo repeated measures data cleaning, include=FALSE}
head(falo_rm)
falo_status_1 <- falo_rm %>%
select(session, status_1)
falo_status_1_plot <- ggplot(falo_status_1, aes(session, status_1)) +
geom_line() +
geom_point(size = 2) +
scale_x_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
scale_y_continuous(limits = c(0, 7),
breaks = c(0, 1, 2, 3, 4, 5, 6, 7)) +
theme_classic() +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "Session",
y = "Number of Nights Per Week Gone to Bed Prior to 12:00 AM",
title = "Status Tracking Goal 1")
falo_status_1_plot
phone_falo <- falo_rm %>%
select(session, num_nights)
phone_falo_graph <- ggplot(phone_falo, aes(session, num_nights)) +
geom_line() +
geom_point(size = 2) +
scale_x_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
scale_y_continuous(limits = c(0, 7),
breaks = c(0, 1, 2, 3, 4, 5, 6, 7)) +
theme_classic() +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "Session",
y = "Number of Nights Per Week Implementing No-Phone Strategy",
title = "No Phone Strategy",
subtitle = "To be implemented 1:00-7:00 AM")
phone_falo_graph
falo_effect <- falo_rm %>%
select(session, effect)
falo_effect_graph <- ggplot(falo_effect, aes(session, effect)) +
geom_line() +
geom_point(size = 2) +
scale_x_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
scale_y_continuous(limits = c(0, 5),
breaks = c(1, 2, 3, 4, 5)) +
theme_classic() +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "Session",
y = "Perceived Effectiveness",
title = "Perceived Effectiveness of No Phone Strategy",
caption = "1 = Not Effective at All\n 2 = Not Effective\n 3 = Somewhat Effective\n 4 = Effective\n 5 = Very Effective")
falo_effect_graph
falo_status_2 <- falo_rm %>%
select(session, status_2)
falo_status_2_plot <- ggplot(falo_status_2, aes(session, status_2)) +
geom_line() +
geom_point(size = 2) +
scale_x_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
scale_y_continuous(limits = c(0, 5),
breaks = c(0, 1, 2, 3, 4, 5)) +
theme_classic() +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "Session",
y = "Number of Missing Assignments per Week",
title = "Status Tracking Goal 2")
falo_status_2_plot
head(falo_rm)
falo_freq_1 <- falo_rm %>%
select(session, planner)
falo_freq_1_plot <- ggplot(falo_freq_1, aes(session, planner)) +
geom_line() +
geom_point(size = 2) +
scale_x_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
scale_y_continuous(limits = c(0, 10),
breaks = c(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
theme_classic() +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "Session",
y = "Number of Weekly Assignments Entered into Calendar",
title = "Frequency of Planner Use")
falo_freq_1_plot
falo_help_1 <- falo_rm %>%
select(session, help_plan)
falo_planner_plot <- ggplot(falo_help_1, aes(session, help_plan)) +
geom_line() +
geom_point(size = 2) +
scale_x_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
scale_y_continuous(limits = c(0, 5),
breaks = c(1, 2, 3, 4, 5)) +
theme_classic() +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "Session",
y = "Perceived Helpfulness",
title = "Perceived Helpfulness of Tracking Assignments in Planner",
caption = "1 = Not Helpful at All\n 2 = Not Helpful\n 3 = Somewhat Helpful\n 4 = Helpful\n 5 = Very Helpful")
falo_planner_plot
falo_freq_2 <- falo_rm %>%
select(session, num_days)
falo_freq_2_plot <- ggplot(falo_freq_2, aes(session, num_days)) +
geom_line() +
geom_point(size = 2) +
scale_x_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
scale_y_continuous(limits = c(0, 7),
breaks = c(0, 1, 2, 3, 4, 5, 6, 7)) +
theme_classic() +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "Session",
y = "Number of Days Per Week Using Time Block Strategy",
title = "Frequency of Time Block Strategy Use")
falo_freq_2_plot
falo_help_2 <- falo_rm %>%
select(session, help_block)
falo_block_plot <- ggplot(falo_help_2, aes(session, help_block)) +
geom_line() +
geom_point(size = 2) +
scale_x_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
scale_y_continuous(limits = c(0, 5),
breaks = c(1, 2, 3, 4, 5)) +
theme_classic() +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "Session",
y = "Perceived Helpfulness",
title = "Perceived Helpfulness of Time Block Strategy",
caption = "1 = Not Helpful at All\n 2 = Not Helpful\n 3 = Somewhat Helpful\n 4 = Helpful\n 5 = Very Helpful")
falo_block_plot
```
```{r falo status 1, include=TRUE}
falo_status_1_plot
```
### Phone Strategy Use
```{r falo phone graph, include=TRUE, fig.align="left"}
phone_falo_graph
```
### Perceived Effectiveness
```{r phone strategy helpfulness, include=TRUE, fig.align="left"}
falo_effect_graph
```
### Status Tracking 2
```{r falo status tracking 2, include=TRUE}
falo_status_2_plot
```
### Planner Use
```{r falo planner use, include=TRUE}
falo_freq_1_plot
```
### Planner Helpfulness
```{r falo planner helpfulness, include=TRUE}
falo_planner_plot
```
### Time Block Use
```{r falo time block use, include=TRUE}
falo_freq_2_plot
```
### Planner Helpfulness
```{r falo time block helpfulness, include=TRUE}
falo_block_plot
```
# DRKAT Outcome
Column {.tabset data-width=650}
-----------------------------------------------------------------------
```{r drkat measures data organization, include=FALSE}
head(outcome)
drkat_brief_2 <- brief_data %>%
filter(client == "DRKAT") %>%
select(client, 22, 23) %>%
rename("Working Memory Pre" = working_memory_pre_self,
"Working Memory Post" = working_memory_post_self) %>%
pivot_longer(
cols = c(2:3),
names_to = "measure",
values_to = "score"
)
drkat <- outcome %>%
filter(client == "DRKAT")
brief_drkat <- drkat %>%
select(1, 16, 17, 20, 21, 32, 33) %>%
rename("Pre Global" = brief_global_pre_self,
"Post Global" = brief_global_post_self,
"Pre BRI" = brief_bri_pre_self,
"Post BRI" = brief_bri_post_self,
"Pre MI" = brief_mi_pre_self,
"Post MI" = brief_mi_post_self) %>%
pivot_longer(
cols = c(2:7),
names_to = "measure",
values_to = "score"
)
drkat_brief_graph <- c("Working Memory Pre", "Working Memory Post")
class_drkat <- drkat %>%
select(client, class_total_pre, class_total_post) %>%
rename("Pre Score" = class_total_pre,
"Post Score" = class_total_post) %>%
pivot_longer(
cols = c(2:3),
names_to = "measure",
values_to = "score"
)
pcss_drkat <- drkat %>%
select(1, c(6:13)) %>%
rename("Feeling Slow Pre" = pcss_pre_feeling_slow,
"Feeling Slow Post" = pcss_post_feeling_slow,
"Feeling Foggy Pre" = pcss_pre_feeling_foggy,
"Feeling Foggy Post" = pcss_post_feeling_foggy,
"Difficulty Concentrating Pre" = pcss_pre_difficulty_concentrating,
"Difficulty Concentrating Post" = pcss_post_difficulty_concentrating,
"Difficulty Remembering Pre" = pcss_pre_difficulty_remembering,
"Difficulty Remembering Post" = pcss_post_difficulty_remembering) %>%
pivot_longer(
cols = c(2:9),
names_to = "measure",
values_to = "score"
)
hit_drkat <- drkat %>%
select(client, hit_pre, hit_post) %>%
rename("Pre Score" = hit_pre,
"Post Score" = hit_post) %>%
pivot_longer(
cols = c(2:3),
names_to = "measure",
values_to = "score"
)
```
```{r drkat plots, include=FALSE}
drkat_brief_plot <- ggplot(drkat_brief_2, aes(measure, score)) +
geom_hline(yintercept = 65,
linetype = "dashed",
size = 1) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = drkat_brief_graph) +
scale_y_continuous(limits = c(0, 100),
breaks = c(10, 20, 30, 40, 50, 60, 70, 80, 90, 100)) +
geom_text(aes(measure, score, label = score),
nudge_y = -3,
color = "white") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
plot.subtitle = element_text(color = "black", size = 10, face = "bold"),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10),
plot.caption = element_text(size = 10)) +
labs(x = "",
y = "T-score",
title = "BRIEF Scores",
subtitle = "Working Memory Scale",
caption = "T-scores Above 65 are Clinically Significant")
drkat_brief_plot
drkat_class_plot <- ggplot(class_drkat, aes(measure, score)) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = class_positions) +
scale_y_continuous(limits = c(0, 60),
breaks = c(10, 20, 30, 40, 50, 60)) +
geom_text(aes(measure, score, label = score),
nudge_y = -3,
color = "white") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "",
y = "Score",
title = "CLASS Scores")
drkat_class_plot
drkat_pcss_plot <- ggplot(pcss_drkat, aes(measure, score)) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = pcss_positions) +
scale_y_continuous(limits = c(0, 6),
breaks = c(0, 1, 2, 3, 4, 5, 6)) +
geom_text(aes(measure, score, label = score),
nudge_y = -1,
color = "white") +
coord_flip() +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10),
plot.caption = element_text(size = 10)) +
labs(x = "",
y = "Score",
title = "PCSS Results",
subtitle = "Cognitive Symptoms",
caption = "0 = No Symptoms\n 3 = Moderate Symptoms\n 6 = Severe Symptoms")
drkat_pcss_plot
drkat_hit_plot <- ggplot(hit_drkat, aes(measure, score)) +
geom_hline(yintercept = 50,
linetype = "dashed",
size = 1) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = hit_positions) +
scale_y_continuous(limits = c(0, 60),
breaks = c(10, 20, 30, 40, 50, 60)) +
geom_text(aes(measure, score, label = score),
nudge_y = -3,
color = "white") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10),
plot.caption = element_text(size = 10)) +
labs(x = "",
y = "Score",
title = "HIT Results",
caption = "Scores of 50 or Greater Suggest Headaches Significantly Impact Daily Functioning")
drkat_hit_plot
```
### BRIEF
```{r drkat brief, include=TRUE, fig.width=6}
drkat_brief_plot
```
### CLASS
```{r drkat class, include=TRUE, fig.width=6}
drkat_class_plot
```
### PCSS
```{r drkat pcss, include=TRUE}
drkat_pcss_plot
```
### HIT
```{r drkat hit, include=TRUE}
drkat_hit_plot
```
Column {data-width=350}
-----------------------------------------------------------------------
### Client Demographics
```{r, include=FALSE}
head(outcome)
demo_drkat <- outcome %>%
filter(client == "DRKAT") %>%
select(2:5)
head(demo_drkat)
drkat_table <- demo_drkat %>%
gt() %>%
cols_label(sex = "Sex",
age = "Age",
prev_mtbi = "Prior Concussions",
hx_depression = "History of Depression or Anxiety") %>%
cols_align(align = "center", columns = vars(sex, age, prev_mtbi, hx_depression)) %>%
tab_header(title = "Client Demographics")
drkat_table
```
```{r drkat table, include=TRUE}
drkat_table
```
# DRKAT Repeated
Column {.tabset data-width=650}
-----------------------------------------------------------------------
### Status Tracking
```{r repeated measures drkat data cleaning, include=FALSE}
head(rm_drkat)
drkat_track <- rm_drkat %>%
select(session, status)
drkat_status_plot <- ggplot(drkat_track, aes(session, status)) +
geom_line() +
geom_point(size = 2) +
scale_x_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
scale_y_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
theme_classic() +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "Session",
y = "Number of House Chores Completed per Week",
title = "Status Tracking Goal")
drkat_status_plot
drkat_effort <- rm_drkat %>%
select(session, effort)
drkat_effort_plot <- ggplot(drkat_effort, aes(session, effort)) +
geom_line() +
geom_point(size = 2) +
scale_x_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
scale_y_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
theme_classic() +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "Session",
y = "Perceived Effort",
title = "Perceived Effort While Completing House Chores",
caption = "1 = No Effort\n 2 = A little Effort\n 3 = Somewhat Effortful\n 4 = Quite Effortful\n 5 = Extremely Effortful")
drkat_motivation <- rm_drkat %>%
select(session, motivation)
drkat_motivation_plot <- ggplot(drkat_motivation, aes(session, motivation)) +
geom_line() +
geom_point(size = 2) +
scale_x_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
scale_y_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
theme_classic() +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "Session",
y = "Perceived Motivation",
title = "Perceived Motivation to Complete House Chores",
caption = "1 = No Motivation\n 2 = A little Motivation\n 3 = Somewhat Motivated\n 4 = Quite Motivated\n 5 = Extremely Motivated")
drkat_freq <- rm_drkat %>%
select(session, frequency)
drkat_freq_plot <- ggplot(drkat_freq, aes(session, frequency)) +
geom_line() +
geom_point(size = 2) +
scale_x_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
scale_y_continuous(limits = c(0, 10),
breaks = c(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
theme_classic() +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "Session",
y = "Number of Tasks Entered into Calendar per Week",
title = "Frequency of Calendar Use")
drkat_help <- rm_drkat %>%
select(session, helpfulness)
drkat_help_plot <- ggplot(drkat_help, aes(session, helpfulness)) +
geom_line() +
geom_point(size = 2) +
scale_x_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
scale_y_continuous(limits = c(0, 5),
breaks = c(1, 2, 3, 4, 5)) +
theme_classic() +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "Session",
y = "Perceived Helpfulness",
title = "Perceived Helpfulness of Calendar",
caption = "1 = Not Helpful at All\n 2 = Not Helpful\n 3 = Somewhat Helpful\n 4 = Helpful\n 5 = Very Helpful")
```
```{r drkat status, include=TRUE}
drkat_status_plot
```
### Perceived Effort
```{r drkat perceived effort, include=TRUE}
drkat_effort_plot
```
### Perceived Motivation
```{r drkat perceived motivation, include=TRUE}
drkat_motivation_plot
```
### Planner Use
```{r drkat perceived frequency of strategy use, include=TRUE}
drkat_freq_plot
```
### Perceived Helpfulness
```{r drkat perceived helpfulness of strategy use, include=TRUE}
drkat_help_plot
```
